Oracle Home Management ‚Äď part 3: Strengths and limitations of Rapid Home Provisioning

In the previous post I mentioned that having a central repository storing the Golden Images would be the best solution for the Oracle Home provisioning.

In this context, Oracle provides Rapid Home Provisioning: a product included in Oracle Grid Infrastructure that automates home provisioning and patching of Oracle Database and Grid Infrastructure Homes, databases and also generic software.

rhp-conceptOracle Rapid Home Provisioning simplifies tremendously the software provisioning: you can use it to create golden images starting from existing installations and then deploy them locally, across different nodes, on local or remote clusters, standalone servers, etc.

Having a central store with enforced naming conventions ensures software standardization across the whole Oracle farm, and makes patching easier with less risks. Also, it allows to patch existing databases, moving them to Oracle Homes with a higher patch level, and taking care of service draining and rolling upgrades when RAC or RAC One Node deployments exist. Multiple databases can be patched in a single batch using one single rhpctl command.

I will not explain the technical details of Rapid Home Provisioning implementation operation. I already did a webinar a couple of years ago for the RAC SIG:

Burt Clouse, the RHP product manager, did a presentation as well about Rapid Home Provisioning 12c Release 2, that highlights some new features that the product was missing in the first release:

More details about the new features can be found here:

https://blogs.oracle.com/db_maintenance/whats-new-in-122-for-rapid-home-provisioning-and-maintenance

Close to be the perfect product, but…

If rapid home provisioning is so powerful, what makes it less appealing for most users?

In my opinion (read: very own personal opinion ūüôā ), there are two main factors:

First: The technology stack RHP is relying on is quite complex

Although Rapid Home Provisioning 12c Release 2 allows Oracle Home deployments on standalone servers (it was not the case with 12c Release 1), the Rapid Home Provisioning sever itself relies on Oracle Grid Infrastructure 12cR2. That means that there must be skills in the company to manage the full stack: Clusterware, ASM, ACFS, NFS, GNS, SCAN, etc. as well as the RHP Server itself.

Second: remote provisioning requires Lifecycle Management Pack (extra-cost) option licensed on all the RHP targets

If Oracle Homes are deployed on the same cluster that hosts the RHP Server, the product can be used at no extra cost. But if you have many clusters, or using standalone servers for your Oracle databases, then RHP can become pricey very quickly: the price per processor for Lifecycle Management Pack is 12’000$, plus support (pricelist April 2018). So, buying this management pack just to introduce Rapid Home Provisioning in your company might be an excessive investment.

Of course, depending on your needs, you can evaluate it and leverage its full potential and make a bigger return of investment.

Or, you might explore if it is viable to configure each cluster as Rapid Home Provisioning Server: in this case it would be free, but it will have the additional complexity layer on all your clusters.

For small companies, simple architectures and especially where Standard Edition is deployed (no Management Pack for Standard Edition!), a self-made, simpler solution might be a better choice.

In the next post, before going into the details of a hypothetical self-made implementation, I will introduce my thoughts about the New Oracle Database Release Model.

 

Oracle Home Management – part 2: Common patching patterns

(*) Multiple times in this blog post I refer to a problem with new Oracle Home installs and rollback scripts. The problem has been fixed with PSU Jan 2017, I did not notice it before, sorry. Thanks to Martin Berger for the information

Let’s see some common approaches to Oracle Home patching.

First, how patches are applied

No, I will not talk about how to use opatch ūüôā It is an overview of the “high-level” methods… when you have multiple servers and (eventually) multiple databases per server.

Worst approach (big bang)

1.Stop everything

2.In-place binaries patching

3.Database patching, “big bang” mode

4.Start everything

With this approach, you have a big downtime, a maintenance window hard to get (all applications are down at the same time), no control over a single database and no easy rollback in case your binaries get compromised/corrupted by the patch apply.

in-place-patching

Another bad approach (new install and out-of-place patching)

1.Re-install binaries manually in a new path

2.Patch the new binaries

3.Stop, change OH, patch databases one by one

4.Decommission old binaries

out-of-place-patchingThis approach is much better than the previous one, but still has some pitfalls:

  • If you have many servers and environments: doing it frequently might be a challenge
  • Rollback scripts are not copied automatically: the datapatch will fail unless you copy them by hand (*)
  • New installs introduce potential human error, unless you use unattended install with your own scripts
  • Do you like to run opatch apply all the time, after all?

Better approach (software cloning)

This approach is very close to the previous one, with the exception that the new Oracle Home is not installed from scratch, but rather cloned from an existing one. This way, the rollback scripts used by the datapatch binary will be there and there will be no errors when patching the databases. (*)

The procedure for Oracle Home cloning is described in the Oracle Documentation, here.

Another cool thing is that you can clone Oracle Homes across different nodes, so that you might have the same patch level everywhere without repeating the tedious tasks of upgrading the opatch, patching the binaries, etc. etc.

But still, you have to identify which Oracle Home you have to clone and keep track of the latest version.

Best approach (Golden Images)

The best approach would consist in having a central repository for your software, where you store every version of your Oracle Homes, one for each patch level.

Having a central repository allows to install the software ONCE and use a “clone, patch and store it” strategy. You can, for example, use only one server to do all the patching and then distribute your software images to the different database servers.

This is the concept of Golden Images used by Rapid Home Provisioning that will be in the scope of my next blog post.

 

Second, which patches are applied

Now that we have seen some Oracle Home patching approaches, is it worth to know which patches are important in a patching strategy.

It is better that you get used to the differences between PSU/BP and RU/RUR, by reading this valuable post from Mike Dietrich:

Differences between PSU / BP and RU / RUR

I will make the assumption that in every case, the critical patches should be applied quarterly, or at least once per year, in order to fix security bugs.

The conservative approach (stability and performance over improvements)

Prior to 12.2, in order to guarantee security and stability, the best approach was to apply only PSUs each quarter.

From 12.2, the most conservative approach is to apply the latest Release Update Review on top of the oldest as possible Release Update. Confusing? Things will be clearer when I’ll write about the 18c New Release Model in a few days…

The cowboy approach (improvements over stability and performance)

Sometimes Bundle Patches and Release Updates contain cool backports from the new releases; sometimes they contain just more bug fixes than the PSUs and RURs; sometimes they fix important stuff like disabling bad transformations that lead to wrong result bugs or other annoying bugs.

Personally, I prefer to include such improvements in my patching strategy: I regularly apply RU for releases >=12.2 and BP for releases <=12.1. Don’t call me cowboy, however ūüôā

The incumbent approach (or why you cannot avoid one-offs)

It does not matter your patch frequency: sometimes you hit a bug, and the only solution is either to apply the one-off patch or the workaround, if available.

If you apply the one-off patch for a specific bug, from an Oracle Home maintenance point of view, it would be better to

  • apply the same one-off everywhere (read, all your Oracle Homes with the very same release), this makes your environment homogeneous.

or

  • use a clone of the Oracle Home with the one-off as basis to apply the release update and distribute it to the other servers.

Why?

Again, it is a problem with rollback scripts (*), with patch conflicts and also, of number of versions to maintain:2018-05-03 16_26_38-Diaporama PowerPoint - [Présentation1]Less paths, less error-prone!

There is, however, the alternative to one-offs: implementing the workaround instead of applying the patch. Most of the time the workaround consist in disabling “something” through parameters, or worse, hidden parameters (the underscore parameters that the support says you should not set, but advise to do¬† all the time as workaround :-))

It might be a good idea to use the workaround instead of apply tha patch if you already know that the bug will be fixed in the next Release Update (for example), or that the workaround is so easy to implement that it is not worth to create another version of Oracle Home that will require special attention at the next quarter.

If you apply workarounds, anyway, be sure that you comment EXACTLY why, when and who, so you can decide to unset it at the next parameter review or maintenance… e.g.

Makes sense?

 

Oracle Home Management – part 1: “Patch soon, patch often” vs. reality

With this post, I am starting a new blog series about Oracle Database home management, provisioning, patching… Best (and worst) practices, common practices and blueprints from my point of view as consultant and, sometimes, as operational DBA.

I hope to find the time to continue (and finish) it ūüôā

How often should you upgrade/patch?

Database patching and upgrading is not an easy task, but it is really important.

Many companies do not have a clear patching strategy, for several reasons.

  • Patching is time consuming
  • It is complex
  • It introduces some risks
  • It is not always really necesary
  • It leads to human errors

Oracle, of course, recommends to apply the patches quarterly, as soon as they are released. But the reality is that it is (still) very common to find customers that do not apply patches regularly.

Look at this:

With January 2018 Bundle Patch, you can fix 1883 bugs, including 56 “wrong results” bugs! I hope I will talk more about this kind of bugs, but for now consider that if you are not patching often, you are taking serious risks, including putting at risk your data consistency.

I will not talk about bugs, upgrade procedures, new releases here… For this, I recommend to follow Mike Dietrich’s blog: Upgrade your Database – NOW!

I would like rather to talk, as the title of this blog series states, about the approaches of maintaining the Oracle Homes across your Oracle server farm.

Common worst practices in maintaining homes

Maintaining a plethora of Oracle Homes across different servers requires thoughtful planning. This is a non-exhaustive list of bad practices that I see from time to time.

  • Installing by hand every new Oracle Home
  • Applying different patch levels on Oracle Homes with the same path
  • Not tracking the installed patches
  • Having Oracle Home paths hard-coded in the operational scripts
  • Not minding about Oracle Home path naming convention
  • Not minding about Oracle Home internal names
  • Copying Oracle Homes without minding about the Central Inventory

All these worst practices lead to what I like to call “patching madness”… that monster that makes regular patching very difficult / impossible.

THIS IS A SITUATION THAT YOU NEED TO AVOID:

A better approach, would be starting having some naming conventions, e.g.:

In the next blog post, I will talk about common patching patterns and their pitfalls.

 

DBMS_AUDIT_MGMT.CLEAN_AUDIT_TRAIL not working on 12c? Here’s why…

It is bad to realize, after a few years, that my customer’s Audit Cleanup procedures are not working properly for every database…

NOTE: The post is based on standard audit, not unified audit.

My customer developed a quite nice procedure for database housekeeping (including diag dest, OS audit trail, recyclebin, DB audit…)

But after some performance problems, I have come across the infamous sql_id 4ztz048yfq32s:

This SQL comes from the “Failed Logon Attempts” metric in Enterprise Manager.

I’ve checked the specific database, and the table SYS.AUD$ was containing way too many rows, dating before our purge time:

The cleanup procedure does basically this:

But despite a retention window of 31 days, the rows are still there:

(today is 27.04.2018, so the oldest records are more than 1 year old)

I’ve checked with ASH, the actual delete statement executed by the clean_audit_trail procedure is:

So, the DBID clause is OK, but the NTIMESTAMP# clause is  not!

Why?

Long story long (hint, it’s a bug: 19958239)
Update 30.05.2018 the solution is explained in this Doc: 2068066.1, thanks John)

The cleanup metadata is stored into the view DBA_AUDIT_MGMT_LAST_ARCH_TS. Its structure in 11g was:

But in 12c, there are 2 new columns:

When the database is upgraded from 11g to 12c, the two new columns are set to “0” by default.

But when the procedure DBMS_AUDIT_MGMT.SET_LAST_ARCHIVE_TIMESTAMP is executed, the actual dbid is used, and new lines appear:

It is clear now that the DELETE statement is not constructed properly. It should get the LAST_ARCHIVE_TS of the actual DBID being purged… but it takes the other one.

According to my tests, it does not use neither the correct timestamp for the dbid, nor get the oldest timestamp: it uses instead the timestamp of the first record found by the clause “WHERE AUDIT_TRAIL=’STANDARD AUDIT TRAIL'”. It depends on the physical location of the row in the table! Clearly a big mess… (PS, not sure 100%, but this is what I suppose)

So, I have tried to modify the archive time for DBID 0:

Trying to execute the cleanup again, now leads to a better timestamp:

I have then tried to play a little bit with the DBA_AUDIT_MGMT_LAST_ARCH_TS view (and the underlying table DAM_LAST_ARCH_TS$).

First, I’ve faked the DBID:

Then, I have tried to increase the retention timestamp (500 days):

Finally, I have tried to purge the audit trail with both DBIDs:

As I expected, in both cases the the cleanup generated the delete with the timestamp of the fake DBID:

Is it possible to delete the unwanted records from the view DBA_AUDIT_MGMT_LAST_ARCH_TS?

Not only is possible, but I recommend it:

Afterwards, the timestamp in the where condition is correct and remains correct after subsequent executions of DBMS_AUDIT_MGMT.SET_LAST_ARCHIVE_TIMESTAMP.

Conclusions, IMPORTANT FOR THE DATABASE OPERATIONS:

The upgrade causes the unwanted lines with DBID=0 in the DBA_AUDIT_MGMT_LAST_ARCH_TS view.

Moreover, any duplicate changes the DBID: any subsequent execution of DBMS_AUDIT_MGMT.SET_LAST_ARCHIVE_TIMESTAMP in the duplicated database will lead to additional lines in the view.

This is what I plan to do now:

  • Whenever I upgrade from 11g to 12c, cleanup the data from DBA_AUDIT_MGMT_LAST_ARCH_TS and schedule the cleanup for DBID 0 as well
  • Whenever I duplicate a database, I execute a DELETE (without clauses) from DBA_AUDIT_MGMT_LAST_ARCH_T and a truncate of the table SYS.AUD$ (it is a duplicate, after all!)

HTH

Basic Vagrantfile for multiple groups of VMs

In case you want to prepare multiple sets of machines quickly using Vagrant, ready for different setups, this might be something for you:

The nice thing, (beside speeding up the creation and basic configuration) is the organization of the directories. The configuration at the beginning of the script will result in 5 virtual machines:

It is based, in part (but modified and simplified a lot), from  the RAC Attack automation scripts by Alvaro Miranda.

I have a more complex version that automates all the¬†tasks for a full multi-cluster RAC environment, but if this is your requirement, I would rather check oravirt scripts on github (https://github.com/oravirt) . They are much more powerful and complete (and complex…) than my Vagrantfile. ūüôā

Cheers

BP and Patch 22652097: set optimizer_adaptive_statistics to FALSE explicitly or it might not work!

Update 14.03.2018: After some exchanges with Nigel Bayliss, the behaviour described here has been filed as unpublished bug 27626925: OPTIMIZER ADAPTIVE STATS DEFAULT FALSE NOT HONORED WHEN ENABLED IN OCT OR JAN BP. It will be fixed starting with April’s bundle patch.

 

According to Nigel’s blog post:

The Oracle 12.1.0.2 October 2017 BP and the Adaptive Optimizer

if you installled the patch 22652097 prior to apply the Bundle Patch 171018, the BP apply in the database should recognize that the patch was already in place and keep it activated. This is done through the fix control 26664361.

When fix_control 26664361:0 -> Patch 22652097 is not enabled: the parameter optimizer_adaptive_features (OAF) works

When fix_control 26664361:1 -> Patch 22652097 is enabled; optimizer_adaptive_features is discarded and the two new parameters have the priority: optimizer_adaptive_plans (OAP) and optimizer_adaptive_statistics (OAS).

But at my customer, I had another behavior.

My patching story might be very similar to yours!

When I started upgrading my customer’s database to 12c in early 2015, I experienced very soon the infamous problems with SQL Plan Directives (SPD) and Adaptive Dynamic Sampling (ADS) that I described in my paper:¬†ADAPTIVE FEATURES OR: HOW I LEARNED TO STOP WORRYING AND TROUBLESHOOT THE BOMB .

Early fixes

When I was new to the problem, the quick fix for the problematic applications was to set OAF to FALSE.

Later, I discovered some more details and decided to opt for setting:

In other cases, I disabled the specific directives that were causing problems.

But many databases did not have so many problems, and I left the defaults.

Patch 22652097 on top of BP170718 

At some point, me and my customer decided to apply the fix 22652097, on top of BP170718 that was our current patch level at that time.

The patch installation on a test database was complaining about the optimizer_adaptive_feature set: this parameter was not used anymore. This issue is nicely explained by Flora in her post Patch 22652097 in 12.1 makes optimizer_adaptive_features parameter obsolete.

In order to apply that patch on the remaining databases, we did:

  • alter system reset optimizer_adaptive_features;
  • alter system reset “_optimizer_dsdir_usage_control”;
  • Applied the patch on binaries and datapatch on the databases.

The result at this point was that:

  • optimizer_adaptive_features was not set
  • optimizer_adaptive_plans was set to true
  • optimizer_adaptive_statistics was set to false.

It might seems superflous to say, but it’s not, the SQL Plan Directives were not used anymore: no Adaptice Dynamic Sampling and no performance problems.

Bundle Patch 180116

Three weeks ago, we installled the last Bundle Patch in order to fix some Grid Infrastructure problems, and the BP, as described in Nigel’s note (and Mike Dietrich and many other bloggers :-)) contains the patch 22652097.

According to Nigel’s post, the patch installation should have detected that the patch 22652097 was already there and activate it.

And indeed, after we applied the BP, the fix_control 26664361 was set to 1 (that means that the patch 22652097 is enabled). So we went live with this setup without additional checks.

One week later, we started experiencing performance problems again. I noticed immediately that the Adaptive Dynamic Sampling was very aggressive again, and the SQL Plan Directives used again.

But the fix was there AND ENABLED!

After a few tests, I realized that the SPD is not used anymore if I set optimizer_adaptive_statistics EXPLICITLY to false.

optimizer_adaptive_statistics must be set explicitly, the default does not work

And here’s the proof:

I use once again the great SPD example by Tim Hall (sorry Tim, it’s not the first time that I steal your work ūüôā ) . You can find here:

SQL Plan Directives in Oracle Database 12c Release 1 (12.1)

After applying the BP, I have the default parameter, not set explicitly, and the fix_control enabled:


If I run the test statement (again, find it here https://oracle-base.com/articles/12c/sql-plan-directives-12cr1) the directives are used:


but then I set the parameter explicitly:

and the SPD usage (and consequently, ADS), are gone:

Conclusion

Set the parameter EXPLICITLY when you apply the BP that contains the fix.

And ALWAYS test the behavior!

You can check how many statements use the dynamic sampling by following this short blog post by Dominic Brooks:

Which of my sql statements are using dynamic sampling?

HTH

My own Dbvisit Replicate integration with Grid Infrastructure

I am helping my customer for a PoC of Dbvisit Replicate as a logical replication tool. I will not discuss (at least, not in this post) about the capabilities of the tool itself, its configuration or the caveats that you should beware of when you do logical replication. Instead, I will concentrate on how we will likely integrate it in the current environment.

My role in this PoC is to make sure that the tool will be easy to operate from the operational point of view, and the database operations, here, are supported by Oracle Grid Infrastructure and cold failover clusters.

Note: there are official Dbvisit  online resources  about how to configure Dbvisit Replicate in a cluster. I aim to complement those informations, not copy them.

Quick overview

If you know Dbvisit replicate, skip this paragraph.

There are three main components of Dbvisit Replicate: The FETCHER, the MINE and the APPLY processes. The FETCHER gets the redo stream from the source and sends it to the MINE process. The MINE process elaborates the redo streams and converts it in proprietary transaction log files (named plog). The APPLY process gets the plog files and applies the transactions on the destination database.

From an architectural point of view, MINE and APPLY do not need to run close to the databases that are part of the configuration. The FETCHER process, by opposite, needs to be local to the source database online log files (and archived logs).

Because the MINE process is the most resource intensive, it is not convenient to run it where the databases reside, as it might consume precious CPU resources that are licensed for Oracle Database. So, first step in this PoC: the FETCHER processes will run on the cluster, while MINE and APPLY will run on a dedicated Virtual Machine.

dbvisit_gi_overview

Clustering considerations

  • the FETCHER does NOT need to run on the server of the source database: having access to the online logs through the ASM instance is enough
  • to avoid SPoF, the fetcher should be a cluster resource that can relocate without problems
  • to simplify the configuration, the FETCHER configuration and the Dbvisit binaries should be on a shared filesystem (the FETCHER does not persist any data, just the logs)
  • the destination database might be literally anywhere: the APPLY connects via SQL*Net, so a correct name resolution and routing to the destination database are enough

so the implementation steps are:

  1. create a shared filesystem
  2. install dbvisit in the shared filesystem
  3. create the Dbvisit Replicate configuration on the dedicated VM
  4. copy the configuration files on the cluster
  5. prepare an action script
  6. configure the resource
  7. test!

Convention over configuration: the importance of a strong naming convention

Before starting the implementation, I decided to put all the caveats related to the FETCHER  resource relocation on paper:

  • Where will the configuration files reside? Dbvisit has an important variable: the Configuration Name. All the operations are done by passing a configuration file named /{PATH}/{CONFIG_NAME}/{CONFIG_NAME}-{PROCESS_TYPE}.ddc to the dbvrep binary. So, I decided to put ALL the configuration directories under the same path: given the Configuration Name, I will always be able to get the configuration file path.
  • How will the configuration files relocate from one node to the other? Easy here: they won’t. I will use an ACFS filesystem
  • How can I link the cluster resource with its configuration name? Easy again: I call my resources dbvrep.CONFIGNAME.PROCESS_TYPE. e.g. dbvrep.FROM_A_TO_B.fetcher
  • How will I manage the need to use a new version of dbvisit in the future? Old and new versions must coexist: Instead of using external configuration files, I will just use a custom resource attribute named DBVREP_HOME inside my resource type definition. (see later)
  • What port number should I use? Of course, many fetchers started on different servers should not have conflicts. This is something that might be either planned or made dynamic. I will opt for the first one. But instead of getting the port number inside the Dbvisit configuration, I will use a custom resource attribute: DBVREP_PORT.

Considerations on the FETCHER listen address

This requires a dedicated paragraph. The Dbvisit documentation suggest to  create a VIP, bind on the VIP address and create a dependency between the FETCHER resource and the VIP. Here is where my configuration will differ.

Having a separate VIP per FETCHER resource might, potentially, lead to dozens of VIPs in the cluster. Everything will depend on the success of the PoC and on how many internal clients will decide to ask for such implementation. Many VIPs == many interactions with network admins for address reservation, DNS configurations, etc. Long story short, it might slow down the creation and maintenance of new configurations.

Instead, each FETCHER will listen to the local server address, and the action script will take care of:

  • getting the current host name
  • getting the current ASM instance
  • changing the settings of the specific Dbvisit Replicate configuration (ASM instance and FETCHER listen address)
  • starting the FETCHER

Implementation

Now that all the caveats and steps are clear, I can show how I implemented it:

Create a shared filesystem

Install dbvisit in the shared filesystem

Create the Dbvisit Replicate configuration on the dedicated VM

Copy the configuration files from the Dbvisit VM to the cluster

Prepare an action script

Configure the resource

Test!

 

Also the relocation worked as expected: when the settings are modified through:

The MINE process get the change dynamically, so no need to restart it.

Last consideration

Adding a hard dependency between the DB and the FETCHER will require to stop the DB with the force option or to always stop the fetcher before the database. Also, the start of the DB will pullup the FETCHER (pullup:always) and the opposite as well. We will consider furtherly if we will use this dependency or if we will manage it differently (e.g. through the action script).

The hard dependency declared without the global keyword, will always start the fetcher on the server where the database runs. This is not required, but it might be nice to see the fetcher on the same node. Again, a consideration that we will discuss furtherly.

HTH

Ludovico

Get the Most out of Oracle Data Guard – The material

Here we go: as usual, the feedback that I usually get after my talks (specifically, after POUG High Five conference), is if I will share my demo scripts and material.

Sadly, the demos I am doing for my presentation “Get the most out of Oracle Data Guard” are quite tied to an environment built for the purpose of the demos. So, do not expect to get scripts easy to use as is, but rather to get some ideas beyond the demo themselves.

I hope they will help to get the whole picture.

Of course, if you need to implement a cloning strategy based on Data Guard or any other solution that I describe in this post, please feel free to contact me, I will be glad to help you implement it in your environment.

Slides

Demo 1

Video:

Scripts:

 

Demo 2

Video:


Scripts:

 

Demo 3

Video:

Scripts:

Preparation:

snap_acfs.pl

 

snap_databasae.pl

clone_from_snap.pl

Cheers

Ludovico

Trivadis sessions at Oracle Open World 2017

This year Trivadis will be again at Oracle Open World (and Oak Table World!) in San Francisco, with a few sessions (including mine!)

If you are going to Oracle Open World and you want to say hello to the Trivadis speakers, make sure you attend them!

Get the Most Out of Oracle Data Guard
Ludovico Caldara – ACE Director, Senior Consultant – Trivadis
When: Sunday, Oct 01, 12:45 PM
Where: Marriott Marquis (Yerba Buena Level) – Nob Hill A/B

EOUC Database ACES Share Their Favorite Database Things
Christian Antognini – ACE Director, OAK Table Member, Senior Principal Consultant, Partner – Trivadis
When: Sunday, Oct 01, 10:45 AM
Where: Marriott Marquis (Golden Gate Level) – Golden Gate C1/C2

Application Containers: Multitenancy for Database Applications
Markus Flechtner – Principal Consultant – Trivadis
When: Sunday, Oct 01, 2:45 PM
Where: Marriott Marquis (Yerba Buena Level) – Nob Hill A/B

TBA
Christian Antognini – ACE Director, OAK Table Member, Senior Principal Consultant, Partner – Trivadis
When: Monday Oct 02, 1:00 PM
Where: Oak Table World, Children Creativity Museum

Apache Kafka: Scalable Message Processing and More
Guido Schmutz – ACE Director, Senior Principal Consultant, Partner – Trivadis
When: Monday Oct 02, 4:30 PM
Where: Moscone West – Room 2004

You can find trivadis’s sessions in the session catalog here.

See you there!

PostgreSQL Large Objects and space usage (part 3)

A blog post series would not be complete without a final post about vacuumlo.

In the previous post we have seen that the large objects are split in tuples containing 2048 bytes each one, and each chunk behaves in the very same way as regular tuples.

What distinguish large objects?
NOTE: in PostgreSQL, IT IS possible to store a large amount of data along with the table, thanks to the TOAST technology. Read about TOAST here.

Large objects are not inserted in application tables, but are threated in a different way. The application using large objects usually has a table with columns of type OID. When the application creates a new large objects, a new OID number is assigned to it, and this number is inserted into the application table.
Now, a common mistake for people who come from other RDBMS (e.g. Oracle), think that a large object is unlinked automatically when the row that references
it is deleted. It is not, and we need to unlink it explicitly from the application.

Let’s see it with a simple example, starting with an empty pg_largeobject table:

Let’s insert a new LOB and reference it in the table t:

Another one:

If we delete the first one, the chunks of its LOB are still there, valid:

If we want to get the rid of the LOB, we have to unlink it, either explicitly or by using triggers that unlink the LOB when a record in the application table is deleted.
Another way is to use the binary vacuumlo included in PostgreSQL.
It scans the pg_largeobject_metadata and search through the tables that have OID columns to find if there are any references to the LOBs. The LOB that are not referenced, are unlinked.
ATTENTION: this means that if you use ways to reference LOBs other than OID columns, vacuumlo might unlink LOBs that are still needed!

vacuumlo has indeed unlinked the first LOB, but the deleted tuples are not freed until a vacuum is executed:

So vacuumlo does not do any vacuuming on pg_largeobject table.